Optimization of the radial basis function neural network spread factor for electrical impedance tomography image reconstruction

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F16%3A86100281" target="_blank" >RIV/61989100:27240/16:86100281 - isvavai.cz</a>
Result on the web
<a href="http://dl.acm.org/citation.cfm?doid=3015166.3015183" target="_blank" >http://dl.acm.org/citation.cfm?doid=3015166.3015183</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3015166.3015183" target="_blank" >10.1145/3015166.3015183</a>

Result language
angličtina
Original language name
Optimization of the radial basis function neural network spread factor for electrical impedance tomography image reconstruction
Original language description
Electrical impedance tomography (EIT) is a low cost, non-invasive imaging technique where the inner resistivity distribution of the investigated object, corresponding to different tissue resistivity, is estimated from voltage measured on the boundary of the this object. The Electrical impedance tomography main problem is to get the resistivity distribution image of a given cross-sectional area based on the boundary voltage measurement. We used Radial basis function (RBF) neural network for image reconstruction in EIT and focused on examining the impact changing spread factor of the RBF to the results of the image reconstruction with the RBF neural network. (C) 2016 ACM.
Czech name
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Czech description
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Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
ACM International Conference Proceeding Series 2016
ISBN
978-1-4503-4790-7
ISSN
—
e-ISSN
—
Number of pages
5
Pages from-to
26-30
Publisher name
ACM
Place of publication
New York
Event location
Auckland
Event date
Nov 21, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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